An Efficient Spectrum Decision Making Framework for Cognitive Radio Networks
B. Dere, and S. Bhujade. International Journal of Innovative Science and Modern Engineering (IJISME), 3 (2):
45-48(January 2015)
Abstract
This review paper is based on the spectrum decision framework for cognitive radio networks. Cognitive radio networks have been proposed as a solution to both spectrum inefficiency and spectrum scarcity problems. However, they face to a unique challenge based on the fluctuating nature of heterogeneous spectrum bands as well as the diverse service requirements of various applications. In this paper, a spectrum decision framework is proposed to determine a set of spectrum bands by considering the application requirements as well as the dynamic nature of spectrum bands. To this end, first, each spectrum is characterized by jointly considering primary user activity and spectrum sensing operations. Based on this, a minimum variance based spectrum decision is proposed for realtime applications, which minimizes the capacity variance of the decided spectrum bands subject to the capacity constraints. For best-effort applications, a maximum capacity-based spectrum decision is proposed where spectrum bands are decided to maximize the total network capacity.
%0 Journal Article
%1 noauthororeditor
%A Dere, Bhagyashree Anil
%A Bhujade, Sheetal
%D 2015
%E Kumar, Dr. Shiv
%J International Journal of Innovative Science and Modern Engineering (IJISME)
%K capacity cognitive decision framework network networks radio scarcity spectrum
%N 2
%P 45-48
%T An Efficient Spectrum Decision Making Framework for Cognitive Radio Networks
%U https://www.ijisme.org/wp-content/uploads/papers/v3i2/B0783013215.pdf
%V 3
%X This review paper is based on the spectrum decision framework for cognitive radio networks. Cognitive radio networks have been proposed as a solution to both spectrum inefficiency and spectrum scarcity problems. However, they face to a unique challenge based on the fluctuating nature of heterogeneous spectrum bands as well as the diverse service requirements of various applications. In this paper, a spectrum decision framework is proposed to determine a set of spectrum bands by considering the application requirements as well as the dynamic nature of spectrum bands. To this end, first, each spectrum is characterized by jointly considering primary user activity and spectrum sensing operations. Based on this, a minimum variance based spectrum decision is proposed for realtime applications, which minimizes the capacity variance of the decided spectrum bands subject to the capacity constraints. For best-effort applications, a maximum capacity-based spectrum decision is proposed where spectrum bands are decided to maximize the total network capacity.
@article{noauthororeditor,
abstract = {This review paper is based on the spectrum decision framework for cognitive radio networks. Cognitive radio networks have been proposed as a solution to both spectrum inefficiency and spectrum scarcity problems. However, they face to a unique challenge based on the fluctuating nature of heterogeneous spectrum bands as well as the diverse service requirements of various applications. In this paper, a spectrum decision framework is proposed to determine a set of spectrum bands by considering the application requirements as well as the dynamic nature of spectrum bands. To this end, first, each spectrum is characterized by jointly considering primary user activity and spectrum sensing operations. Based on this, a minimum variance based spectrum decision is proposed for realtime applications, which minimizes the capacity variance of the decided spectrum bands subject to the capacity constraints. For best-effort applications, a maximum capacity-based spectrum decision is proposed where spectrum bands are decided to maximize the total network capacity.},
added-at = {2021-09-21T09:41:40.000+0200},
author = {Dere, Bhagyashree Anil and Bhujade, Sheetal},
biburl = {https://www.bibsonomy.org/bibtex/29e3f677386d2a9b145563014ef7c293e/ijisme_beiesp},
editor = {Kumar, Dr. Shiv},
interhash = {0d0fcbfe650538e9ba86426566fcd810},
intrahash = {9e3f677386d2a9b145563014ef7c293e},
issn = {2319-6386},
journal = {International Journal of Innovative Science and Modern Engineering (IJISME)},
keywords = {capacity cognitive decision framework network networks radio scarcity spectrum},
language = {En},
month = {January},
number = 2,
pages = {45-48},
timestamp = {2021-09-21T09:41:40.000+0200},
title = {An Efficient Spectrum Decision Making Framework for Cognitive Radio Networks},
url = {https://www.ijisme.org/wp-content/uploads/papers/v3i2/B0783013215.pdf},
volume = 3,
year = 2015
}